Erythropoiesis is a fundamental process in vertebrate animals and has long served as a paradigm for molecular investigations of developmental regulation. It has been well established that a small number of transcription factors, also known as master regulators, play an essential role in the maintenance of cell-identity and/or regulate the cell differentiation process. However, it is not fully elucidated how they work in combination with each other or various cofactors, particularly at different developmental stages. Since there are at least a thousand transcriptional regulators in mammals, the number of possible combinations is astronomical. Using experimental methods alone to dissect such complexity remains a daunting task as it demands prohibitively high cost and labor. To overcome this challenge, we propose a systems biology approach to be carried out by a team of experienced experimental and computational biologists. Using human primary erythroid precursor cells as the model system, we will generate extensive experimental data by genomic, epigenomic, and transcriptomic profiling, develop data-integrative and predictive computational methods, and perturb the systems by disrupting the normal regulatory activities. Our preliminary work has identified important regulatory network differences between adult and fetal erythroid precursors and suggested that collaboration between master regulators and cofactors plays an important role in driving developmental stage-specific transcriptional changes through acting upon enhancer elements. This will be extended by focusing on the following specific aims: (1) Predict and validate the developmental stage-specific gene regulatory networks in human primary erythroid precursors by integrating genomic and epigenomic data-types; (2) Perturb the gene regulatory networks using molecular and genetic experiments and further integrate such information to refine our network model; (3) Characterize the role of genetic variants influencing chromatin state, gene expression, and erythroid traits. In the end our results will greatly expand our current mechanistic understanding of combinatorial control in establishing cell-type and developmental stage-specificity and provide functional insights into erythroid trait- associated genetic variants.